Editing IPCC:AR6/WGIII/Chapter-11 (section)

== 11.2 New Trends in Emissions and Industrial Development ==

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=== 11.2.1 Major Drivers ===

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The use of materials is deeply coupled with economic development and growth. For centuries, humanity has been producing and using hundreds of materials ( [[#Ashby--2012|Ashby 2012]] ), the diversity of which skyrocketed in the recent half-century to achieve the desired performance and functionality of multiple products (density; hardness; compressive strength; melting point, resistance to mechanical and thermal shocks and to corrosion; transparency; heat- or electricity conductivity; chemical neutrality or activity, to name a few). New functions drive the growth of material complexity of products; for example, a modern computer chip embodies over 60 different elements ( [[#Graedel--2015|Graedel et al. 2015]] ).

Key factors driving up industrial GHG emissions since 1900 include population and per capita GDP, [[#footnote-025|2]] while energy efficiency and non-combustion GHG emissions intensity (from industrial processes and waste) has been pushing it down. Material efficiency factors – material stock intensity of GDP and ratio of extraction, processing and recycling of materials per unit of built capital along with combustion-related emissions intensity factors and electrification – were cyclically switching their contributions with relatively limited overall impact. Growing recycling allowed for replacement of some energy-intensive virgin materials and thus contributed to mitigation. In 2014–2019, a combination of these drivers allowed for a slowdown in the growth of industrial GHG emissions to below 1% (Figure 11.2 and Table 11.1), while to match a net zero emissions trajectory it should decline by 2% yr –1 in 2020–2030 and by 8.9% yr –1 in 2030–2050 ( [[#IEA--2021a|IEA 2021a]] ).

'''Table 11.1 | Dynamics and structure of industrial greenhouse gas (''' '''GHG) emissions.'''

{| class="wikitable"
|-
! rowspan="2"|
! colspan="4"| Average annual growth rates

! colspan="5"| Share in total industrial sector emissions

! rowspan="2"| 2019 emissions MtCO 2 -eq

|-
! 1971–1990

! 1991–2000

! 2000–2010

! 2011–2019

! 1970

! 1990

! 2000

! 2010

! 2019

|-
| rowspan="8"| Direct CO 2 emissions from fuel combustion

| Mining (excl. fuels), manufacturing industries and construction

| 0.13%

| –0.18%

| 4.62%

| 0.77%

| 45.8%

| 37.3%

| 33.2%

| 36.6%

| 34.9%

| 6981

|-
| Iron and steel

| 0.20%

| 0.13%

| 5.62%

| 2.28%

| 12.4%

| 10.2%

| 9.4%

| 11.4%

| 12.4%

| 2481

|-
| Chemical and petrochemical

| 3.66%

| 1.54%

| 3.16%

| 1.19%

| 3.0%

| 4.9%

| 5.2%

| 4.9%

| 4.9%

| 977

|-
| Non-ferrous metals

| 2.12%

| 3.20%

| 1.12%

| 1.36%

| 0.7%

| 0.8%

| 1.0%

| 0.8%

| 0.8%

| 163

|-
| Non-metallic minerals

| 2.91%

| 1.88%

| 6.24%

| –0.04%

| 3.3%

| 4.6%

| 5.0%

| 6.5%

| 5.7%

| 1148

|-
| Paper, pulp and printing

| 0.78%

| 2.79%

| 0.09%

| –2.69%

| 1.4%

| 1.3%

| 1.5%

| 1.1%

| 0.7%

| 150

|-
| Food and tobacco

| 2.55%

| 1.50%

| 3.03%

| –1.04%

| 1.3%

| 1.6%

| 1.7%

| 1.6%

| 1.3%

| 265

|-
| Other

| –1.55%

| –2.89%

| 4.61%

| –0.22%

| 23.8%

| 13.8%

| 9.4%

| 10.3%

| 9.0%

| 1797

|-
| colspan="2"| Indirect emissions – electricity

| 2.87%

| 2.06%

| 3.00%

| –0.87%

| 17.6%

| 24.6%

| 27.3%

| 25.8%

| 21.2%

| 4236

|-
| colspan="2"| Indirect emissions – heat

| 2.08%

| –3.09%

| 2.53%

| 9.83%

| 5.6%

| 6.7%

| 4.5%

| 4.0%

| 8.3%

| 1663

|-
| rowspan="5"| Industrial processes CO 2

| Total

| 1.45%

| 2.16%

| 5.00%

| 1.93%

| 11.0%

| 11.6%

| 13.0%

| 14.9%

| 15.7%

| 3144

|-
| Non-metallic minerals

| 2.22%

| 2.36%

| 5.66%

| 1.67%

| 5.7%

| 7.0%

| 8.0%

| 9.7%

| 10.0%

| 2008

|-
| Chemical and petrochemical

| 4.51%

| 2.52%

| 3.50%

| 2.01%

| 1.5%

| 2.9%

| 3.4%

| 3.4%

| 3.6%

| 720

|-
| Metallurgy

| –3.11%

| 0.37%

| 5.16%

| 3.10%

| 3.6%

| 1.5%

| 1.4%

| 1.7%

| 2.0%

| 391

|-
| Other

| 1.55%

| 2.30%

| –1.21%

| 2.89%

| 0.1%

| 0.2%

| 0.2%

| 0.1%

| 0.1%

| 25

|-
| colspan="2"| Industrial product use GHG

| –0.22%

| –0.49%

| –1.02%

| 0.41%

| 2.7%

| 2.0%

| 1.7%

| 1.1%

| 1.0%

| 204

|-
| colspan="2"| Other non-CO 2 GHG

| –0.60%

| 5.20%

| 4.29%

| 3.20%

| 5.5%

| 3.9%

| 5.8%

| 6.2%

| 7.3%

| 1470

|-
| colspan="2"| Waste GHG

| 1.94%

| 1.35%

| 1.22%

| 1.57%

| 11.9%

| 13.8%

| 14.4%

| 11.4%

| 11.6%

| 2327

|-
| colspan="2"| Total GHG

| 1.16%

| 0.98%

| 3.61%

| 1.32%

| 100.0%

| 100.0%

| 100.0%

| 100.0%

| 100.0%

| 20,025

|}

Source: calculated based on [[#Crippa--2021|Crippa et al. (2021)]] ; [[#IEA--2021b|IEA (2021b)]] ; and [[#Minx--2021|Minx et al. (2021)]] .

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[[File:1d07a1feb00df3989ed9df2859b0b4fb IPCC_AR6_WGIII_Figure_11_2.png]]

'''Figure 11.2 | Average annual growth rates of industrial sector GHG emissions and drivers (''' '''1900–2019''' ''').''' '''Before 1970, GHG emission (other) is limited to that from cement production. Waste emission is excluded. Primary material extraction excludes fuels and biomass. Presented factors correspond directly to Equation 11.1.''' Sources: population before 1950 and GDP before 1960: [[#Maddison%20Project--2018|Maddison Project (2018)]] ; population from 1950 to 1970: [[#UN--2015|UN (2015)]] ; population and GDP for 1960–2020: [[#World%20Bank--2021|World Bank (2021)]] ; data on material stock, extraction, and use of secondary materials: [[#Wiedenhofer--2019|Wiedenhofer et al. (2019)]] ; data on material extraction: UNEP and IRP (2020); industrial energy use for 1900–1970: [[#IIASA--2018|IIASA (2018)]] , for 1971–2019: [[#IEA--2021b|IEA (2021b)]] ; data on industrial GHG emissions for 1900–1970: [[#CDIAC--2017|CDIAC (2017)]] , for 1970–2019: data from [[#Crippa--2021|Crippa et al. (2021)]] and [[#Minx--2021|Minx et al. (2021)]] .

There are two major concepts of '''material efficiency''' ( ''ME'' ). The broader one highlights demand reduction via policies promoting more intensive use, assuming sufficient (excluding luxury) living space or car ownership providing appropriate service levels – housing days or miles driven and life-time extension ( [[#Hertwich--2019|Hertwich et al. 2019]] , 2020). This approach focuses on dematerialisation of society ( [[#Lechtenböhmer--2020|Lechtenböhmer and Fischedick 2020]] ), where a ‘dematerialisation multiplier’ ( [[#Pauliuk--2021|Pauliuk et al. 2021]] ) limits both material stock and GDP growth, as progressively fewer materials are required to build and operate the physical in-use stock to deliver sufficient services. According to the IRP (2020), reducing floor space demand by 20% via shared and smaller housing compared to the reference scenario would decrease Group of Seven (G7) countries’ GHG emissions from the material-cycle of residential construction up to 70% in 2050. The narrower concept ignores demand and sufficiency aspects and focuses on supply chains considering ''ME'' as less basic materials use to produce a certain final product, for example, a car or a metre squared of living space ( [[#OECD--2019a|OECD 2019a]] ; [[#IEA--2020a|IEA 2020a]] ). No matter if the broader or the narrower concept of ''ME'' is applied, in 1970–2019 it did not contribute much to the decoupling of industrial emissions from GDP. This is expected to change in the future ( ).

Material efficiency analysis mostly uses material intensity or productivity indicators, which compare material extraction or consumption with GDP ( [[#Oberle--2019|Oberle et al. 2019]] ; [[#Hertwich--2020|Hertwich et al. 2020]] ). Those indicators are functions of '''material stock intensity of GDP''' (tonnes per dollar) and material intensity of building and operating accumulated in-use stock. Coupling services or GDP with the built stock allows for a better evaluation of demand for primary basic materials ( [[#Müller--2011|Müller et al. 2011]] ; [[#Liu--2013|Liu et al. 2013]] ; Liu and Müller 2013; [[#Pauliuk--2013a|Pauliuk et al. 2013a]] ; [[#Cao--2017|Cao et al. 2017]] ; [[#Wiedenhofer--2019|Wiedenhofer et al. 2019]] ; [[#Hertwich--2020|Hertwich et al. 2020]] ; [[#Krausmann--2020|Krausmann et al. 2020]] ). Since 1970 material stock growth driven by industrialisation and urbanisation slightly exceeded that of GDP and there was no decoupling, [[#footnote-024|3]] so in Kaya-like identities material stock may effectively replace GDP. There are different methods to estimate the former (see reviews in Pauliuk et al. (2015, 2019) and [[#Wiedenhofer--2019|Wiedenhofer et al. (2019)]] , the results of which are presented for major basic materials with some geographical resolution (Liu and Müller 2013; [[#Pauliuk--2013a|Pauliuk et al. 2013a]] ) or globally ( [[#Graedel--2011|Graedel et al. 2011]] ; [[#Geyer--2017|Geyer et al. 2017]] ; [[#Krausmann--2018|Krausmann et al. 2018]] ; [[#Pauliuk--2019|Pauliuk et al. 2019]] ; [[#Wiedenhofer--2019|Wiedenhofer et al. 2019]] ; [[#International%20Aluminium%20Institute--2021a|International Aluminium Institute 2021a]] ).

For a subset of materials, such as solid wood, paper, plastics, iron/steel, aluminium, copper, other metals/minerals, concrete, asphalt, bricks, aggregate, and glass, total in-use stock escalated from 36 Gt back in 1900 to 186 Gt in 1970, 572 Gt in 2000, and 960 Gt in 2015, and by 2020 it exceeded 1,100 Gt, or 145 tonnes per capita ( [[#Krausmann--2018|Krausmann et al. 2018]] , 2020; [[#Wiedenhofer--2019|Wiedenhofer et al. 2019]] ). In 1900–2019, the stock grew 31-fold, which is strongly coupled with GDP growth (36-fold). As the UK experience shows, material stock intensity of GDP may ultimately decline after services fully dominate GDP, and this allows for material productivity improvements to achieve absolute reduction in material use, as stock expansion slows down ( [[#Streeck--2020|Streeck et al. 2020]] ). While the composition of basic materials within the stock of manufactured capital was evolving significantly, overall stock use associated with a unit of GDP has been evolving over the last half-century in a quite narrow range of 7.7–8.6 t per USD1000 (2017 purchasing power parity (PPP)) showing neither signs of decoupling from GDP, nor saturation as of yet. Mineral building materials (concrete, asphalt, bricks, aggregate, and glass) dominate the stock volume by mass (94.6% of the whole stock, with the share of concrete alone standing at 43.5%), followed by metals (3.5%) and solid wood (1.4%). The largest part of in-use stock of our ‘cementing societies’ ( [[#Cao--2017|Cao et al. 2017]] ) is constituted by concrete: about 417 Gt in 2015; [[#Krausmann--2018|Krausmann et al. (2018)]] extrapolated this to 478 Gt (65 tonnes per capita) in 2018, which contains about 88 Gt of cement. [[#footnote-023|4]] The iron and steel stock is assessed at 25–35 Gt ( [[#Wiedenhofer--2019|Wiedenhofer et al. 2019]] ; [[#Gielen--2020|Gielen et al. 2020]] ; [[#Wang--2021|Wang et al. 2021]] ), while the plastics stock reached 2.5–3.2 Gt ( [[#Geyer--2017|Geyer et al. 2017]] ; [[#Wiedenhofer--2019|Wiedenhofer et al. 2019]] ; [[#Saygin--2021|Saygin and Gielen 2021]] ) and the aluminium stock approached 1.1 Gt ( [[#International%20Aluminium%20Institute--2021a|International Aluminium Institute 2021a]] ), or just 0.1% of the total. In sharp contrast to global energy intensity, which has more than halved since 1900 ( [[#Bashmakov--2019|Bashmakov 2019]] ), in 2019 material stock intensity (in-use stock of manufactured capital per GDP) was only 14% below the 1900 level, but 15% above the 1970 level. In-use stock per capita has been growing faster than GDP per capita since 2000 (Figure 11.3). The growth rate of total in-use stock of manufactured capital was 3.8% in 1971–2000 and 3.5% in 2000–2019, or 32–35 Gt yr –1 , to which concrete and aggregates contributed 88%. Recent demand for stockbuilding materials was 51–54 Gt yr –1 , to which recycled materials recently contributed only about 10% of material input. About 46–49 Gt yr –1 was virgin inputs, which after accounting for processing waste and short-lived products (over 8 Gt yr –1 ) scale up to 54–58 Gt yr –1 of primary extraction ( [[#Krausmann--2017|Krausmann et al. 2017]] , 2018; UNEP and IRP 2020). The above indicates that we have only begun to exploit the potential for recycling and circularity more broadly.

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[[File:1ebf27a395e7140fdda4da1818d94e00 IPCC_AR6_WGIII_Figure_11_3.png]]

'''Figure 11.3 | Raw natural materials extraction since 1970.''' In windows: left – growth of population, GDP and basic materials production (1990 = 100) in 1990–2020; right – in-use stock per capita vs income level (1900–2018; brown dots are for 2000–2018). The regressions provided show that for more recent years elasticity of material stock to GDP was greater than unity, comparing with the lower unity in preceding years. Source: developed based on [[#Maddison%20Project--2018|Maddison Project (2018)]] ; [[#Wiedenhofer--2019|Wiedenhofer et al. (2019)]] ; [[#IEA--2020b|IEA (2020b)]] ; UNEP and IRP (2020); [[#International%20Aluminium%20Institute--2021a|International Aluminium Institute (2021a)]] ; Statista (2021a,b); U.S. Geological Survey (2021); [[#World%20Bank--2021|World Bank (2021)]] ; [[#World%20Steel%20Association--2021|World Steel Association (2021)]] .

Total '''extraction of all basic materials''' (including biomass and fuels) in 2017 reached 92 Gt yr –1 , which is 13 times above the 1900 level (Figure 11.3). [[#footnote-022|5]] When recycled resources are added, total material inputs exceed 100 Gt ( [[#Circle%20Economy--2020|Circle Economy 2020]] ). In Equation 11.1 ''MPR'' represents only material inputs to the stock, excluding dissipative use – biomass (food and feed) and combusted fuels. Total extraction of stock building materials (metal ores and non-metallic minerals) in 2017 reached 55 Gt yr –1 . [[#footnote-021|6]] In 1970–2018, it grew 4.3-fold and the ratio of ''MPR'' to accumulated in-use capital has nearly been constant since 1990 along with ratio to GDP (Figure 11.3).

End-of-life waste from accumulated stocks along with (re)-manufacturing and construction waste is assessed at 16 Gt yr –1 in 2014 and can be extrapolated in 2018 to 19 Gt yr –1 ( [[#Krausmann--2018|Krausmann et al. 2018]] ; [[#Wiedenhofer--2019|Wiedenhofer et al. 2019]] ), or 1.8% from stock of manufactured capital. Less than 6 Gt yr –1 was recycled and used to build the stock (about 10% of inputs). [[#footnote-020|7]] While the circularity gap is still large, and limited circularity was engineered into accumulated stocks, [[#footnote-019|8]] '''material recycling''' mitigated some GHG emissions by replacing energy-intensive virgin materials. [[#footnote-018|9]] When the stock saturates, in closed material loops the end-of-life materials waste has to be equal to material input, and primary production therefore has to be equal to end-of-life waste multiplied by unity minus recycling rate. When the latter grows, as the linear metabolism is replaced with the circular one, the share of primary materials production in total material input declines.

Recycling rates for metals are higher than for other materials: the end-of-life scrap input ratio for 13 metals is over 50%, and stays in the range of 25–50% for another ten, but even for metals recycling flows fail to match the required inputs ( [[#Graedel--2011|Graedel et al. 2011]] ). Globally, despite overall recycling rates being at 85%, the all-scrap ratio for steel production in recent years stays close to 35–38% ( [[#Gielen--2020|Gielen et al. 2020]] ; [[#IEA--2021b|IEA 2021b]] ) ranging from 22% in China (only 10% in 2015) to 69% in the US and to 83% in Turkey ( [[#BIR--2020|BIR 2020]] ). For end-of-life scrap this ratio declined from 30% in 1995–2010 to 21–25% after 2010 ( [[#Gielen--2020|Gielen et al. 2020]] ; [[#Wang--2021|Wang et al. 2021]] ).

For aluminium, the share of scrap-based production grew from 17% in 1962 to 34% in 2010 and stabilised at this level until 2019, while the share of end-of-life scrap grew from 1.5% in 1962 to nearly 20% in 2019 ( [[#International%20Aluminium%20Institute--2021a|International Aluminium Institute 2021a]] ). The global recycling (mostly mechanical) rate for plastics is only 9–10% [[#footnote-017|10]] ( [[#Geyer--2017|Geyer et al. 2017]] ; [[#Saygin--2021|Saygin and Gielen 2021]] ), and that for paper progressed from 34% in 1990 to 44% in 2000 and to over 50% in 2014–2018 ( [[#IEA--2020b|IEA 2020b]] ).

The limited impacts of material efficiency factors on industrial GHG emissions trends reflect the lack of integration of material efficiency in energy and climate policies which partly results from the inadequacy of monitored indicators to inform policy debates and set targets; [[#footnote-016|11]] lack of high-level political focus and industrial lobbying; uncoordinated policy across institutions and sequential nature of decision-making along supply chains; carbon pricing policy lock-in with upstream sectors failing to pass carbon costs on to downstream sectors (due to compensation mechanisms to reduce carbon leakage) and so have no incentives to exploit such options as light-weighting, reusing, remanufacturing, recycling, diverting scrap, extending product lives, using products more intensely, improving process yields, and substituting materials ( [[#Skelton--2017|Skelton and Allwood 2017]] ; [[#Gonzalez%20Hernandez--2018b|Gonzalez Hernandez et al. 2018b]] ; [[#Hilton--2018|Hilton et al. 2018]] ). Poor progress with material efficiency is part of the reason why industrial GHG emissions are perceived as ‘hard to abate’, and many industrial low-carbon trajectories to 2050 leave up to 40% of emissions in place ( [[#Material%20Economics--2019|Material Economics 2019]] ; [[#IEA--2021a|IEA 2021a]] ). The importance of this factor activation rises as in-use material stock is expected to scale up by a factor of 2.2–2.7 to reach 2215–2720 Gt by 2050 ( [[#Krausmann--2020|Krausmann et al. 2020]] ). Material extraction in turn is expected to rise to 140–200 Gt yr –1 by 2060 ( [[#OECD--2019a|OECD 2019a]] ; [[#Hertwich--2020|Hertwich et al. 2020]] ) providing unsustainable pressure on climate and environment and calling for fundamental improvements in material productivity.

In 2014–2019, the average annual growth rate (AAGR) of global '''industrial energy use''' was 0.4% compared to 3.2% in 2000–2014, following new policies and trends, particularly demonstrated by China [[#footnote-015|12]] ( [[#IEA--2020b|IEA 2020b]] ,d). Whatever metric is applied, industry (coal transformation, mining, quarrying, manufacturing and construction) driven mostly by material production, dominates global energy consumption. About two fifths of energy produced globally goes to industry, directly or indirectly. Direct energy use (including energy used in coal transformation) accounts for nearly 30% of total final energy consumption. When supplemented by non-energy use, the share for the post-AR5 period (2015–2019) stands on average close to 40% of final energy consumption, and at 28.5% of primary energy use. [[#footnote-014|13]] With an account of indirect energy use for the generation of power and centralised heat to be consumed in industry, the latter scales up to 37%. Industrial energy use may be split by: material production and extraction (including coal transformation): 51% on average for 2015–2019; non-energy use (mostly chemical feedstock): 22% [[#footnote-013|14]] ; and other energy use (equipment, machinery, food and tobacco, textiles, leather, etc.): 27%. Energy use for material production and feedstock [[#footnote-012|15]] makes about three quarters (73%) of industrial energy consumption and is responsible for 77% of its increment in 2015–2019 (based on [[#IEA--2021a|IEA 2021a]] ).

For over a century, '''industrial energy efficiency''' improvements have partially offset growth in GHG emissions. Industrial energy use per tonne of extracted materials (ores and building materials as a proxy for materials going through the whole production chain to final products) fell by 20% in 2000–2019 and by 15% in 2010–2019, accelerated driven by high energy prices to 2.4% yr –1 in 2014–2019, matching the values observed back in 1990–2000 (Figure 11.2). Assessed per value added using market exchange rates, industrial energy intensity globally dropped by 12% in 2010–2018, after its 4% decline in 2000–2010, resulting in 2000–2018 decline by 15% ( [[#IEA--2020b|IEA 2020b]] ,a). The 2020 COVID crisis slowed down energy intensity improvements by shifting industrial output towards more energy-intensive basic materials ( [[#IEA--2020e|IEA 2020e]] ). Specific energy consumption per tonne of iron and steel, chemicals and cement production in 2019 was about 20% below the 2000 level ( [[#IEA--2020b|IEA 2020b]] ,a). This progress is driven by moving towards best available technologies (BATs) for each product through new and highly efficient production facilities in China, India and elsewhere, and by the contribution from recycled scrap metals, paper and cardboard.

Physical energy intensity for the production of materials typically declines and then stabilises at the BAT level once the market is saturated, unless a transformative new technology enters the market ( [[#Gutowski--2013|Gutowski et al. 2013]] ; [[#Crijns-Graus--2020|Crijns-Graus et al. 2020]] ; [[#IEA--2021a|IEA 2021a]] ). Thus, the energy saving effect of switching to secondary used material comes to the forefront, as energy consumption per tonne for many basic primary materials approach the BATs. This highlights the need to push towards circular economy, materials efficiency, reduced demand, and fundamental process changes (e.g., towards electricity and hydrogen-based steel making). Improved recycling rates allow for a substantial reduction in energy use along the whole production chain – material extraction, production, and assembling – which is in great excess of energy used for collection, separation, treatment, and scrap recycling minus energy used for scrap landfilling. The International Energy Agency ( [[#IEA--2019b|IEA 2019b]] ) estimates that by increasing the recycling content of fabricated metals, average specific energy consumption (SEC) for steel and aluminium may be halved by 2060. Focusing on whole systems ‘integrative design’ expands efficiency resource much beyond the sum of potentials for individual technologies. Material efficiency coupled with energy efficiency can deliver much greater savings than energy efficiency alone. [[#Gonzalez%20Hernandez--2018b|Gonzalez Hernandez et al. (2018b)]] stress that presently about half of steel or aluminium are scrapped in production or oversized for targeted services. They show that resource efficiency expressed in exergy as a single metric for both material and energy efficiency for the global iron and steel sector is only 33%, while secondary steel-making is about twice as efficient (66%) as ore-based production (29%). While shifting globally in ore-based production from the average to the best available level can save 6.4 EJ yr –1 , the saving potential of shifting to secondary steel-making is 8 EJ yr –1 , and is limited mostly by scrap availability and steel quality requirements.

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=== 11.2.2 New Trends in Emissions ===

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GHG emissions attributable to the industrial sector (see Chapter 2) in 2019 originate from industrial fuel combustion (7.1 GtCO 2 -eq directly and about 5.9 Gt indirectly from electricity and heat generation [[#footnote-011|16]] ); industrial processes (4.5 GtCO 2 -eq) and products use (0.2 Gt), as well as from waste (2.3 Gt) (Figure 11.4a,b). Overall industrial direct GHG emissions amount to 14.1 GtCO 2 -eq (Figure 11.4c and Table 11.1), and scales up to 20 GtCO 2 -eq after indirect emissions are added, [[#footnote-010|17]] putting industry (24%, direct emissions) second after the energy sector in total GHG emissions and lifting it to the leading position after indirect emissions are allocated (34% in 2019). [[#footnote-009|18]] The corresponding shares for 1990–2000 were 21% for direct emissions and 30% for both direct and indirect ( [[#Crippa--2021|Crippa et al. 2021]] ; [[#Lamb--2021|Lamb et al. 2021]] ; [[#Minx--2021|Minx et al. 2021]] ). As the industrial sector is expected to decarbonise slower than other sectors it will keep this leading position for the coming decades ( [[#IEA--2021a|IEA 2021a]] ). In 2000–2010, total industrial emissions grew faster (3.8% yr –1 ) than in any other sector (see Chapter 2), mostly due to the dynamics shown by basic materials extraction and production. Industry contributed nearly half (45%) of overall incremental global GHG emissions in the 21st century.

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[[File:256e42faa24898291e62cef70c5802f5 IPCC_AR6_WGIII_Figure_11_4.png]]

'''Figure 11.4 | Industrial sector direct global greenhouse gas (GHG) emissions.''' Source: calculated based on emissions data from [[#Crippa--2021|Crippa et al. (2021)]] and [[#Minx--2021|Minx et al. (2021)]] . Indirect emissions were assessed using [[#IEA--2021b|IEA (2021b)]] . For (e): [[#Cao--2020|Cao et al. (2020)]] ; IEA (2020b, 2021a); [[#GCCA--2021a|GCCA (2021a)]] ; [[#International%20Aluminium%20Institute--2021a|International Aluminium Institute (2021a)]] ; and [[#Wang--2021|Wang et al. (2021)]] .

Industrial sector GHG emissions accounting is complicated by carbon storage in products ( [[#Levi--2018|Levi and Cullen 2018]] ). About 35% of chemicals’ mass is CO 2 , which is emitted at use stage – decomposition of fertilisers, or plastic waste incineration ( [[#Saygin--2021|Saygin and Gielen 2021]] ), and sinks. Recarbonation and mineralisation of alkaline industrial materials and wastes (also known as the ‘sponge effect’) provide 0.6–1 GtCO 2 yr –1 uptake by cement-containing products [[#footnote-008|19]] ( [[#Cao--2020|Cao et al. 2020]] ; [[#Guo--2021|Guo et al. 2021]] ); see [[#11.3.6|Section 11.3.6]] for further discussion in decarbonisation context.

In 1970–1990, industrial direct combustion-related emissions were growing modestly, and in 1990–2000 even switched to a slowly declining trend, steadily losing their share in overall industrial emissions. Electrification was the major driver behind both indirect and total industrial emissions in those years. This quiet evolution was interrupted in the beginning of the 21st century, when total emissions increased by 60–68% depending on the metric applied (the fastest growth ever seen). In 2000–2019 iron, steel and cement absolute GHGs increased more than any other period in history ( [[#Bashmakov--2021|Bashmakov 2021]] ). Emissions froze temporarily in 2014–2016, partly in the wake of the financial crisis, but returned to their growth trajectory in 2017–2019 (Figure 11.4a).

The largest incremental contributors to industrial emissions in 2010–2019 were industrial processes at 40%, then indirect emissions (25%), and only then direct combustion (21%), followed by waste (14%; Figure 11.4). Therefore, to stop emission growth and to switch to a zero-carbon pathway more mitigation efforts should be focused on industrial processes, product use and waste decarbonisation, along with the transition to low-carbon electrification ( [[#Hertwich--2020|Hertwich et al. 2020]] ).

Basic materials production dominates both direct industrial GHG emissions (about 62%, waste excluded) [[#footnote-007|20]] as well as direct industrial CO 2 emissions (70%), led by iron and steel, cement, chemicals, and non-ferrous metals (Figure 11.4e). Basic materials also contribute 60% to indirect emissions. In a zero-carbon power world, with industry lagging behind in the decarbonisation of high-temperature processes and feedstock, it may replace the energy sector as the largest generator of indirect emissions embodied in capital stock. [[#footnote-006|21]] According to [[#Circle%20Economy--2020|Circle Economy (2020)]] and [[#Hertwich--2020|Hertwich et al. (2020)]] , GHG emissions embodied in buildings and infrastructure, machinery and transport equipment exceed 50% of their present carbon footprint.

In 1970–2000, direct GHG emissions per unit of energy showed a steady decline interrupted by noticeable growth in 2001–2018 driven by the fast expansion of steel and cement production (Figure 11.5; [[#IEA--2021a|IEA 2021a]] ). Non-energy-related GHG emissions per unit of extracted materials decline continuously, as the share of not carbon intensive building materials (aggregates and sand) grows.

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[[File:cf3f7286d8afe224629cdff9d9345fe2 IPCC_AR6_WGIII_Figure_11_5.png]]

'''Figure 11.5 | Industrial sector greenhouse gas (GHG) emissions in 10 world regions (''' '''1990–2019''' ''').''' Source: calculated based on emissions data from [[#Crippa--2021|Crippa et al. (2021)]] . Indirect emissions were assessed using [[#IEA--2021b|IEA (2021b)]] .

|Iron and steel carbon intensity stagnated in 1995–2015 due to rapid growth in carbon-intensive production in some countries ( [[#Wang--2021|Wang et al. 2021]] ). For aluminium carbon intensity declined in 2010–2019 by only 2% ( [[#International%20Aluminium%20Institute--2021a|International Aluminium Institute 2021a]] ). The carbon intensity of cement-making since 2010 is down by only 4%. In 1990–2019 it fell by 19.5%, mostly due to energy efficiency improvements (by 18.5%) as the carbon intensity of the fuel mix declined only by 3% ( [[#GCCA--2021b|GCCA 2021b]] ). Historical analysis shows the carbon intensity of steel production has declined with ‘stop and go’ patterns in 50–60-year cycles, reflective of the major jumps in best available technology (BAT). From 1900 to 1935 and from 1960 to 1990 specific scope 1 + 2 + 3 emissions fell by 1.5–2.5 tCO 2 per tonne, or as much as needed now to achieve net zero. While historical declines were mostly due to commissioning large capacities with new technologies, with total emissions growing, by 2050 and beyond the decline will likely materialise via new ultra-low emission capacity replacements pushing absolute emissions to net zero ( [[#Bataille--2021b|Bataille et al. 2021b]] ).

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=== 11.2.3 Industrial Development Patterns and Supply Chains (Regional) ===

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The dramatic increase in industrial emissions after 2000 is clearly associated with economic growth in Asia, which dominated both absolute and incremental emissions ( a,b).

More recent 2010 to 2019 trends show that regional contributions to additional emissions are distributed more evenly, while a large part still comes from Asian countries, where both rates of economic growth and the share of industrial emissions much exceed the global average. All other regions also contributed to total industrial GHG emissions. Structural shifts towards emissions from industrial processes and products use are common for many regions ( a).

'''Economic development.''' Regional differences in emission trends are determined by the differences observed in economic development, trade and supply chain patterns. The major source of industrial emissions is production of energy-intensive materials, such as iron and steel, chemicals and petrochemicals, non-ferrous metals and non-metallic products. Steel and cement are key inputs to urbanisation and infrastructure development (buildings and infrastructure are responsible for about three fourths of the steel stock). Application of a ‘services-stock-flow-emissions’ perspective ( [[#Wiedenhofer--2019|Wiedenhofer et al. 2019]] ; [[#Bashmakov--2021|Bashmakov 2021]] ; [[#Haberl--2021|Haberl et al. 2021]] ) shows that relationship patterns between stages of economic development, per capita stocks and flows of materials are not trivial with some clear transition points. [[#Cao--2017|Cao et al. (2017)]] mapped countries by four progressive stages in cement stock per capita S-shape evolution as a function of income and urbanisation: initial stage for developing countries with a low level and slow linear growth; take-off stage with accelerated growth; slowdown stage; and finally a shrinking stage (represented by just a few countries with very high incomes exceeding 40,000 USD2010 per capita) and urbanisation levels above 80%. [[#Bleischwitz--2018|Bleischwitz et al. (2018)]] use a similar approach with five stages to study material saturation effects for apparent consumption and stocks per capita for steel, cement, aluminium, and copper. This logic may be generalised to other materials from which in-use stock is built. While globally cement in-use stock is about 12 tonnes per capita, in developed countries it is 15–30 tonnes per capita, but the order of magnitude is lower in developing states with high per capita escalation rates ( [[#Cao--2017|Cao et al. 2017]] ). When stocks for some materials saturate – per capita stock peaks – the ‘scrap age’ is coming ( [[#Pauliuk--2013a|Pauliuk et al. 2013a]] ). Steel in-use stock has already saturated in advanced economies at 14 ± 2 tonnes per capita due to largely completed urbanisation and infrastructure developments, and a switch towards services-dominated economy. This saturation level is three to four times that of the present global average, which is below 4 tonnes per capita ( [[#Pauliuk--2013a|Pauliuk et al. 2013a]] ; [[#Graedel--2011|Graedel et al. 2011]] ; [[#Wiedenhofer--2019|Wiedenhofer et al. 2019]] ). China is entering the maturing stage of steel and cement consumption, resulting in a moderate projection of additional demand followed by expected industrial emissions peaking in the next 10 to 15 years ( [[#Zhou--2013|Zhou et al. 2013]] ; [[#Bleischwitz--2018|Bleischwitz et al. 2018]] ; [[#OECD--2019a|OECD 2019a]] ; [[#Wu--2019|Wu et al. 2019]] ; [[#Zhou--2020|Zhou et al. 2020]] ). But many developing countries are still urbanising, and the growing need for infrastructure services results in additional demand for steel and cement. Materials intensity of the global economy is projected by [[#OECD--2019a|OECD (2019a)]] to decline at 1.3% yr –1 until 2060, driven by improving resource efficiency and the switch to circular economy, but with a projected tripling of global GDP it means a doubling of projected materials use ( [[#OECD--2019a|OECD 2019a]] ). Under the business-as-usual scenario, India’s demand for steel may more than quadruple over the next 30 years ( [[#de%20la%20Rue%20du%20Can--2019|de la Rue du Can et al. 2019]] ; [[#Dhar--2020|Dhar et al. 2020]] ). In the [[#IEA--2021a|IEA (2021a)]] net-zero-energy scenario, the saturation effect along with material efficiency counterbalances activity effects and keeps demand growth for basic materials modest while escalate demand for critical materials (copper, lithium, nickel, graphite, cobalt and others).

'''International trade and supply chain.''' In Equation 11.1 the share of allocated emissions ( ''Dm'' ) equals unity when territorial emission is considered, and to the ratio of domestically used materials to total material production for consumption-based emission accounting. Tracking consumption-based emissions provides additional insights in the global effectiveness of national climate policies. Carbon emissions embodied in international trade are estimated to account for 20–30% of global carbon emissions ( [[#Meng--2018|Meng et al. 2018]] ; [[#OECD.Stat--2019|OECD.Stat 2019]] ) and are the reason for different emissions patterns of OECD versus non-OECD countries (Chapter 2).

Based on [[#OECD.Stat--2019|OECD.Stat (2019)]] datasets, 2015 CO 2 emissions embodied in internationally traded industrial products (manufacturing and mining, excluding fuels) by all countries are assessed at 3 GtCO 2 , or 30% of direct CO 2 emissions in the industrial sector as reported by [[#Crippa--2021|Crippa et al. (2021)]] . OECD countries collectively have reduced territorial emissions (shares of basic materials in direct emissions in those regions decline ( b), but demonstrated no progress in reducing outsourced emissions embedded in imported industrial products ( [[#Arto--2014|Arto and Dietzenbacher 2014]] ; [[#OECD.Stat--2019|OECD.Stat 2019]] ). Accounting for net carbon emissions embodied in international trade of only industrial products (1283 million tCO 2 in 2015) escalates direct OECD industrial CO 2 emissions (1333 million tCO 2 of energy-related and 502 million tCO 2 of industrial processes) 1.7 fold, 2.3-fold for the US, 1.5-fold for the EU, and more than triples it for the UK, while cutting ( ''Dm'' ) by a third for China and Russia ( [[#OECD.Stat--2019|OECD.Stat 2019]] ; [[#IEA--2020f|IEA 2020f]] ). In most OECD economies, the amount of CO 2 embodied in net import from non-OECD countries is equal to, or even greater than, the size of their Paris 2030 emissions reduction commitments. In the UK, the Parliament Committee on Energy and Climate Change requested that a consumption-based inventory be complementarily used to assess the effectiveness of domestic climate policy in delivering absolute global emissions reductions ( [[#Barrett--2013|Barrett et al. 2013]] ; [[#UKCCC--2019a|UKCCC 2019a]] ). It should be noted that the other side of the coin is that exports from countries with lower production carbon intensities can lead to overall less emissions than if production took place in countries with high carbon intensities, which may become critical in the global evolution toward lower emissions. The evolution of ''Dm'' to the date was driven mostly by factors other than carbon regulation often equipped with carbon leakage prevention tools. Empirical tests have failed to date to detect meaningful ‘carbon leakage’ and impacts of carbon prices on net import, direct foreign investments, volumes of production, value added, employment, profits, and innovation in industry ( [[#Sartor--2013|Sartor 2013]] ; [[#Branger--2016|Branger et al. 2016]] ; Saussay and Sato 2018; [[#Ellis--2019|Ellis et al. 2019]] ; [[#Naegele--2019|Naegele and Zaklan 2019]] ; [[#Acworth--2020|Acworth et al. 2020]] ; [[#Carratù--2020|Carratù et al. 2020]] ; [[#Pyrka--2020|Pyrka et al. 2020]] ; [[#Zachmann--2020|Zachmann and McWilliams 2020]] ). In the coming years, availability of large low-cost renewable electricity potential and cheap hydrogen may become a new driver for relocation of such carbon intensive industries as steel production ( [[#Bataille--2020a|Bataille 2020a]] ; [[#Gielen--2020|Gielen et al. 2020]] ; [[#Bataille--2021a|Bataille et al. 2021a]] ; [[#Saygin--2021|Saygin and Gielen 2021]] ).

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